The demand for the latest AI models for the analysis of strictly protected video streams, which are easily deployed to the cloud, is growing. There is a need for a trusted market ecosystem that allows for secure interaction with resource providers. By using decentralized applications, we can achieve operational transparency and increase user trust in the system. In this master's thesis, we presented backend, frontend and orchestration technologies needed to develop decentralized applications and proposed an architecture that integrates many components. We described an interactive web application for video stream analysis that allows the user to run a selected AI model to analyze their own video stream. Key data is stored on the smart contract, and data from external systems is obtained from the oracle. Kubernetes deploys AI models on infrastructure in the form of containers. Compared to related works, it is distinguished by the monetization of services, trust in the system, accessibility of methods and the possibility of edge computing, which represents the advancement of the state of the art in the field. The application developed in this master's thesis can serve as an example of good practice for further research work in the field of decentralized application development. It demonstrates how we can integrate blockchain, container orchestration, AI and web user interfaces.
|
